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Using trading ratios to correct for ...

Liu, Wenbo.

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Using trading ratios to correct for systematic selection in performance-based water quality trading programs.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Using trading ratios to correct for systematic selection in performance-based water quality trading programs./
作者:	Liu, Wenbo.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2015,
面頁冊數:	51 p.
附註:	Source: Masters Abstracts International, Volume: 55-03.
Contained By:	Masters Abstracts International55-03(E).
標題:	Agricultural economics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10014937
ISBN:	9781339488653

Using trading ratios to correct for systematic selection in performance-based water quality trading programs.
Liu, Wenbo.

Using trading ratios to correct for systematic selection in performance-based water quality trading programs. - Ann Arbor : ProQuest Dissertations & Theses, 2015 - 51 p.

Source: Masters Abstracts International, Volume: 55-03.

Thesis (M.S.)--University of Delaware, 2015.

Scientific-based water quality models are used in water quality trading programs to assess nutrient loadings. Maryland Nutrient Trading Tool (MDNTT) calculates loading reductions on a land use, land cover map of all fields in the Maryland and Delaware portion of the Chesapeake Bay Watershed for a host of potential best management practices (BMPs). However, uncertainty remains. This work hypothesizes that the BMP projects with largest overestimated abatement error would be supplied first into trading program, which is called as a "first-worst" selection. An algorithm is developed to perform the simulation of abatement error and four alternative systematic selection mechanisms: "first-worst" selection, "first-best", acreage targeting and benefits targeting. There are 100 treatments consisting of 10 possible levels of abatement heterogeneity and 10 possible levels of budget. The rule of prioritization of the four mechanisms is different. The outputs of the simulation experiment are the sum of error, the proportion of error of selected projects, and the predicted values of the percentage of error from nonlinear model estimation. As for "first-worst" selection, the results show that there is a convex relationship between error and the budget ratio. Holding heterogeneity constant and in each level of heterogeneity, total error of selected projects will increase as the budget ratio increase from 10% to 50%, reaching the peak value, and then it will decrease as budget ratio continues to rise. Holding the budget constant, the error will experience an unstable growth as heterogeneity increases. The results offer an empirical estimate of how best to vary trading ratios. When it comes to "first-best" selection, the results show that under the largest level of abatement heterogeneity and in a thin market, there is 50% more abatement than the estimates. This indicates that if policymakers can target those underestimated projects, they can expect more abatement than estimation with just a small amount of budget. However, trading cannot achieve the "first-best" solution due to the information asymmetry. The results of two targeting strategies show that benefit targeting can be regarded as a "second-best" solution.

ISBN: 9781339488653Subjects--Topical Terms:

3172150
Agricultural economics.

Using trading ratios to correct for systematic selection in performance-based water quality trading programs.
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